Lifestyle and clinical risk factors in relation with the prevalence of diabetes in the Indonesian urban and rural populations: The 2018 Indonesian Basic Health Survey.

Aims: To investigate the differences between Indonesian urban and rural populations in the association of lifestyle and clinical factors with diabetes prevalence. Methods: Using database of the 2018 Indonesian Basic Health Survey, which was conducted in April-May 2018, non-pregnant respondents aged ≥15 years old with available blood glucose data (n urban = 17,129, n rural = 16,585) were included in this study. The diagnosis of diabetes was based on the combination of known diabetes, i.e., a previous history of diabetes or use of anti-diabetes medication, and unknown diabetes based on blood glucose criteria. We performed logistic regression analyses separately for the urban and rural populations to examine the association of lifestyle and clinical factors with prevalent diabetes. Results: Indonesian urban population was less physically active, had a lower proportion of adequate fruit and vegetable intake, and had higher individuals with obesity than rural population. Although there were no differences in the total prevalence of diabetes between the two populations (10.9 % vs. 11.0 %, for urban and rural, respectively), the prevalence of known diabetes was twice higher in urban than in rural population (3.8 % vs. 1.9 %). Physical activity was associated with lower risk of diabetes, especially in the urban population [prevalence OR (95 %CI): 0.91 (0.85; 0.98) for urban and 0.94 (0.89; 1.00) for rural). Obesity, hypertension, and dyslipidemia were risk factors for prevalent diabetes in both populations. Conclusions: Indonesian rural population showed relatively better lifestyle and clinical profiles compared to their urban counterparts. However, no differences were observed between the two populations in the relation between risk factors and diabetes. Special attention needs to be addressed to the high prevalence of undiagnosed and untreated diabetes in Indonesia.

Adherence to the healthy lifestyle guideline in relation to the metabolic syndrome: Analyses from the 2013 and 2018 Indonesian national health surveys.

In this study, we aimed to investigate differences in lifestyle factors and prevalence of metabolic syndrome (MetS) in the Indonesian population between 2013 and 2018. In addition, we investigated whether adherence to the 2015-released national healthy lifestyle guideline ('GERMAS') is associated with MetS in different sex, age, urban/rural, and BMI categories. We performed cross-sectional analyses in individuals aged >15 of the 2013 (n = 34,274) and 2018 (n = 33,786) Indonesian National Health Surveys. A stratified, multi-stage, systematic random sampling design and the probability proportional to size method were used to select households in the 34 provinces across the country. MetS was defined according to the Joint Interim Statement Criteria, and adherence to 'GERMAS' guideline was defined as fulfilling the national healthy lifestyle recommendations of ≥150 min/week physical activity (PA), ≥5 portions/day fruit and vegetable (FV), no smoking (NS), and no alcohol consumption (NA). We examined the associations of each lifestyle factor with MetS using logistic regression categorised by sex, age groups, urban/rural, and BMI, and adjusted for sociodemographic factors. We observed that men who adhered to the guideline had lower odds ratio of MetS [OR(95%CI) associated with PA: 0.85(0.75-0.97); NA: 0.75(0.56-1.00)] than non-adherent men. Middle-aged adults who adhered to the guideline had lower OR of MetS [PA: 0.85(0.72-1.01); FV: 0.78(0.62-0.99); NA: 0.66(0.46-0.93)] than non-adherent adults <45 years. The adherent urban population had lower OR of MetS [FV: 0.85(0.67-1.07); NA: 0.74(0.52-1.07)] than the non-adherent urban population. Those with overweight or obesity who adhered to the guideline had relatively lower odds of MetS than those who did not. In conclusion, in this nationally representative study, adherence to the 'GERMAS' guideline may confer cardiometabolic health benefits to several groups of the Indonesian population, particularly men, middle-aged, those with overweight and obesity, and potentially urban population.

Illness perceptions and health-related quality of life in individuals with overweight and obesity.

INTRODUCTION: To understand how individuals (self-)manage obesity, insight is needed into how patients perceive their condition and how this perception translates into health outcomes (e.g., health-related quality of life, HRQOL). Our objectives were (1) to examine illness perceptions in individuals with overweight and obesity, and (2) to investigate associations of these perceptions with physical and mental HRQOL. METHODS: In a cross-sectional analysis of the Netherlands Epidemiology of Obesity Study (n = 6432; 52% women), illness perceptions were assessed using the Brief Illness Perception Questionnaire, and HRQOL was assessed using the 36-Item Short-Form Health Survey. Illness perceptions were calculated for different categories of overall, abdominal, and metabolically unhealthy obesity. We investigated associations of illness perceptions with HRQOL using BMI-stratified multivariable linear regression analyses. RESULTS: Compared to individuals with normal weight, individuals with obesity believed to a higher extent that their condition had more serious consequences [Mean Difference (95%CI): 1.8 (1.6-2.0)], persisted for a longer time [3.4 (3.2-3.6)], manifested in more symptoms [3.8 (3.6-4.0)], caused more worry [4.2 (3.9-4.4)] and emotional distress [2.0 (1.8-2.2)], but was more manageable with medical treatment [3.1 (2.9-3.4)]. They perceived to a lesser extent that they had personal control [-2.2 (-2.4, -2.0)] and understanding [-0.3 (-0.5, -0.1)] regarding their condition. These negative perceptions were less pronounced in individuals with abdominal obesity. Behaviour/Lifestyle was attributed by 73% of participants to be the cause of their obesity. Stronger negative illness perceptions were associated with impaired HRQOL, particularly the physical component. CONCLUSION: Individuals with obesity perceived their conditions as threatening, and this seemed somewhat stronger in individuals with overall obesity than those with abdominal obesity. Behaviour/Lifestyle is a crucial target intervention and empowering self-management behaviour to achieve a healthy body weight may deliver promising results. In addition, strategies that aim to change negative perceptions of obesity into more adaptive ones may improve HRQOL.

The associations of leptin and adiponectin with the metabolic syndrome in an Indonesian and a Dutch population.

BACKGROUND AND AIMS: At the same BMI, Asian populations develop cardiometabolic complications earlier than Western populations. We hypothesized that a different secretion of the adipocyte-derived hormones leptin and adiponectin plays a role and investigated the associations of the two hormones with the metabolic syndrome (MetS) in an Indonesian and a Dutch population. METHODS AND RESULTS: We performed cross-sectional analyses of the Netherlands Epidemiology of Obesity Study (n = 6602) and the SUGAR Scientific Programme Indonesia-Netherlands Study (n = 1461). We examined sex-stratified associations of leptin and adiponectin with MetS, using multivariate logistic regression including adjustment for total body fat. The mean (SD) leptin (mcg/L) were 4.7 (6.0) in Indonesian men, 18.6 (12.0) in Indonesian women, 9.1 (7.7) in Dutch men, and 23.4 (17.4) in Dutch women. The mean (SD) adiponectin (mg/L) were 5.7 (5.4), 7.5 (7.1), 6.6 (3.3), and 11.3 (4.9), respectively. Within the same BMI category, leptin concentrations were similar in the two populations, whereas adiponectin was lower in the Indonesian population. Per SD of leptin, adjusted prevalence odds ratios (ORs, 95%CI) of MetS were 0.9 (0.6-1.2) in Indonesian men, 1.1 (0.9-1.4) in Indonesian women, 2.2 (1.6-2.8) in Dutch men, and 1.2 (1.0-1.5) in Dutch women. Per SD of adiponectin, the ORs were 0.9 (0.7-1.2), 0.8 (0.7-1.0), 0.6 (0.6-0.8), and 0.4 (0.4-0.5), respectively. CONCLUSIONS: Despite lower adiponectin levels, adiponectin was not related to the MetS in the Indonesian population and can not explain their increased cardiometabolic risk at the same BMI.

The prevalence of metabolic syndrome and its association with body fat distribution in middle-aged individuals from Indonesia and the Netherlands: a cross-sectional analysis of two population-based studies.

BACKGROUND: The prevalence of metabolic syndrome varies among populations with different ethnicities. Asian populations develop metabolic complications at lower amounts of adiposity than western populations. The role of abdominal obesity in the metabolic differences between the two populations is poorly understood. OBJECTIVES: Our objectives were to estimate the prevalence of metabolic syndrome and the relative contribution of its components in the Indonesian and the Dutch population, as well as to examine the associations of overall and abdominal obesity with metabolic syndrome. METHODS: In this cross-sectional study of middle-aged adults in the Netherlands Epidemiology of Obesity Study (n = 6602) and the Indonesian National Health Surveillance (n = 10,575), metabolic syndrome was defined by the unified IDF and AHA/NHLBI criteria. We performed logistic and linear regressions to examine associations of BMI and waist circumference with the metabolic syndrome, mutually adjusted for waist circumference and BMI. RESULTS: The prevalence of metabolic syndrome was 28% and 46% in Indonesian men and women, and 36% and 24% in Dutch men and women. The most prominent components were hypertension (61%) and hyperglycemia (51%) in the Indonesian, and hypertension (62%) and abdominal obesity (40%) in the Dutch population. Per SD in BMI and waist circumference, odds ratios (ORs, 95% CI) of metabolic syndrome were 1.5 (1.3-1.8) and 2.3 (1.9-2.7) in Indonesian men and 1.7 (1.2-2.5) and 2.9 (2.1-4.1) in Dutch men. The ORs of metabolic syndrome were 1.4 (1.2-1.6) and 2.3 (2.0-2.7) in Indonesian women and 1.0 (0.8-1.3) and 4.2 (3.2-5.4) in Dutch women. CONCLUSION: More Indonesian women than men have metabolic syndrome, whereas the opposite is true for the Dutch population. In both the Indonesian and the Dutch populations, hypertension is the primary contributor to the prevalence of metabolic syndrome. In both populations, abdominal adiposity was more strongly associated with metabolic syndrome than overall adiposity.